Violent radicalization during the COVID-19 pandemic: at the intersection of gender, conspiracy theories and psychological distress
Bibliographic record
Abstract
The COVID-19 pandemic continues to pose a threat to health, economic stability and collective functioning. The related upsurge in psychological distress has fuelled the emergence of conspiracy theories regarding the origins of the virus. Worldwide, there is mounting evidence that these narratives have increased stigma and discrimination against diverse ethnic, age and occupational groups. However, the role of gender in the dynamics weaving together psychological distress, conspiracy theories and legitimation of violence toward other groups is still unknown. This paper addresses this knowledge gap, analysing a Canadian interprovincial survey conducted in November 2020. In total, 6003 individuals aged 18-35 years residing in large Canadian cities responded to an online survey administered in English and French between October 16 and November 17, 2020. A total of 4928 individuals with complete data on support for violent radicalization (VR), psychological distress, and endorsement of COVID-19 conspiracy theories were included in the analysis. This study indicates that for young Canadian adults, gender, endorsement of COVID-19 conspiracy theories and psychological distress, as measured by the Hopkins Symptom Checklist-25 (HSCL-25), have an interaction effect on support for VR, as measured by both the Sympathy for Violent Radicalization Scale (SyfoR) and the Radicalism Intention Scale (RIS) (both p-values <.001). While the magnitude of the association between support for VR and endorsement of COVID-19 conspiracy theories is greatest among individuals with scores of psychological distress above the clinical cut-off, there is a significant association between scores on support for VR and endorsement of COVID-19 conspiracy theories in both women and men, both above and below the psychological distress cut-off of the HSCL-25. Effective strategies to mitigate the relationship between violent radicalization and pandemic-related psychological distress must explicitly address gender differences in expression and management of psychological distress.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".